Kinect microphone array-based speech and speaker recognition for the exhibition control of humanoid robots

Ding, Ing-Jr; Shi, Junqin

doi:10.1016/j.compeleceng.2015.12.010

Cited by 39 publications

(21 citation statements)

References 8 publications

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“…Context, tone, pitch and loudness all combine to convey information. Research regarding speech understanding in robotics include works like [24,25], etc. In addition to vocalization, facial expressions, also give an insight into the intent of the social agent.…”

Section: Cognition and Perceptionmentioning

confidence: 99%

Socially Believable Robots

Moetesum¹,

Siddiqi²

2018

Human-Robot Interaction - Theory and Application

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Long-term companionship, emotional attachment and realistic interaction with robots have always been the ultimate sign of technological advancement projected by sci-fi literature and entertainment industry. With the advent of artificial intelligence, we have indeed stepped into an era of socially believable robots or humanoids. Affective computing has enabled the deployment of emotional or social robots to a certain level in social settings like informatics, customer services and health care. Nevertheless, social believability of a robot is communicated through its physical embodiment and natural expressiveness. With each passing year, innovations in chemical and mechanical engineering have facilitated lifelike embodiments of robotics; however, still much work is required for developing a "social intelligence" in a robot in order to maintain the illusion of dealing with a real human being. This chapter is a collection of research studies on the modeling of complex autonomous systems. It will further shed light on how different social settings require different levels of social intelligence and what are the implications of integrating a socially and emotionally believable machine in a society driven by behaviors and actions.

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Section: Cognition and Perceptionmentioning

confidence: 99%

Socially Believable Robots

Moetesum¹,

Siddiqi²

2018

Human-Robot Interaction - Theory and Application

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“…Speech is one of the most frequently utilized communication manners in humans' daily life. Speech recognition is widely employed to identify the operator [7] [10] and extract the emotions of human beings [8] [9] to communicate with social robots and service robots. Speech instructions are also recognized to program industrial robots [6].…”

Section: Introductionmentioning

confidence: 99%

An Online Robot Teaching Method using Static Hand Gestures and Poses

Sun¹,

Zhang²,

Chen³

et al. 2021

Preprint

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With an increasing number of robots are employed in manufacturing, a human-robot interaction method that can teach robots in a natural, accurate, and rapid manner is needed. In this paper, we propose a novel human-robot interface based on the combination of static hand gestures and hand poses. In our proposed interface, the pointing direction of the index finger and the orientation of the whole hand are extracted to indicate the moving direction and orientation of the robot in a fast-teaching mode. A set of hand gestures are designed according to their usage in humans' daily life and recognized to control the position and orientation of the robot in a fine-teaching mode. We employ the feature extraction ability of the hand pose estimation network via transfer learning and utilize attention mechanisms to improve the performance of the hand gesture recognition network. The inputs of hand pose estimation and hand gesture recognition networks are monocular RGB images, making our method independent of depth information input and applicable to more scenarios. In the regular shape reconstruction experiments on the UR3 robot, the mean error of the reconstructed shape is less than 1 mm, which demonstrates the effectiveness and efficiency of our method.

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“…Dynamic time warping (DTW) measures the similarity by warping two time series on the time axis to find the optimal alignment among all possible alignments [28]. Accordingly, DTW has been widely used in many fields such as gesture, image, and speech recognition [29]- [32], intrusion detection [33], financial analysis [34], biometrics [35], and medical diagnosis [36]. However, standard DTW, which considers all possible alignments, requires a quadratic time complexity with the lengths of two time series [43].…”

Section: Introductionmentioning

confidence: 99%